irrlicht/source/lib/json/tools/serve_header/README.md

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serve_header.py
===============
Serves the `single_include/nlohmann/json.hpp` header file over HTTP(S).
The header file is automatically amalgamated on demand.
![serve_header.py demo](demo.png)
## Prerequisites
1. Make sure these Python packages are installed.
```
PyYAML
watchdog
```
(see `tools/serve_header/requirements.txt`)
2. To serve the header over HTTPS (which is required by Compiler Explorer at this time), a certificate is needed.
The recommended method for creating a locally-trusted certificate is to use [`mkcert`](https://github.com/FiloSottile/mkcert).
- Install the `mkcert` certificate authority into your trust store(s):
```
$ mkcert -install
```
- Create a certificate for `localhost`:
```
$ mkcert localhost
```
The command will create two files, `localhost.pem` and `localhost-key.pem`, in the current working directory. It is recommended to create them in the top level or project root directory.
## Usage
`serve_header.py` has a built-in default configuration that will serve the `single_include/nlohmann/json.hpp` header file relative to the top level or project root directory it is homed in.
The built-in configuration expects the certificate `localhost.pem` and the private key `localhost-key.pem`to be located in the top level or project root directory.
To start serving the `json.hpp` header file at `https://localhost:8443/json.hpp`, run this command from the top level or project root directory:
```
$ make serve_header
```
Open [Compiler Explorer](https://godbolt.org/) and try it out:
```cpp
#include <https://localhost:8443/json.hpp>
using namespace nlohmann;
#include <iostream>
int main() {
// these macros are dynamically injected into the header file
std::cout << JSON_BUILD_TIME << " (" << JSON_BUILD_COUNT << ")\n";
return 0;
}
```
> `serve_header.py` dynamically injects the macros `JSON_BUILD_COUNT` and `JSON_BUILD_TIME` into the served header file. By comparing build count or time output from the compiled program with the output from `serve_header.py`, one can be reasonably sure the compiled code uses the expected revision of the header file.
## Configuration
`serve_header.py` will try to read a configuration file `serve_header.yml` in the top level or project root directory, and will fall back on built-in defaults if the file cannot be read.
An annotated example configuration can be found in `tools/serve_header/serve_header.yml.example`.
## Serving `json.hpp` from multiple project directory instances or working trees
`serve_header.py` was designed with the goal of supporting multiple project roots or working trees at the same time.
The recommended directory structure is shown below but `serve_header.py` can work with other structures as well, including a nested hierarchy.
```
json/ ⮜ the parent or web server root directory
├── develop/ ⮜ the main git checkout
│ └── ...
├── feature1/
│ └── ... any number of additional
├── feature2/ ⮜ working trees (e.g., created
│ └── ... with git worktree)
└── feature3/
└── ...
```
To serve the header of each working tree at `https://localhost:8443/<worktree>/json.hpp`, a configuration file is needed.
1. Create the file `serve_header.yml` in the top level or project root directory of any working tree:
```yaml
root: ..
```
By shifting the web server root directory up one level, the `single_include/nlohmann/json.hpp` header files relative to each sibling directory or working tree will be served.
2. Start `serve_header.py` by running this command from the same top level or project root directory the configuration file is located in:
```
$ make serve_header
```
`serve_header.py` will automatically detect the addition or removal of working trees anywhere within the configured web server root directory.